The present invention relates to radio communications systems, and more particularly to techniques for measuring an amount of time dispersion associated with a received radio signal.
Dispersion is the process by which radiation is separated in accordance with some characteristic (e.g., frequency, wavelength, energy) into components which have different directions. It is well known that when a radio signal is transmitted, its dispersed energy components may individually reflect off of different objects in the radio environment, so that a number of energy components will take different paths to arrive at a receiver. Because the different paths are generally of different lengths, the reflected energy components arrive at the receiver at correspondingly different times. This phenomenon is called multipath propagation.
This multipath characteristic causes a transmitted radio pulse to undergo different gain and phase variations resulting in reception of a distorted pulse. Pulse distortion from the channel medium can cause, for example, interference between adjacent samples of the received signal resulting in a phenomenon known as intersymbol interference. Intersymbol interference can be viewed as a smearing of the transmitted pulse by the multi-path, causing overlap between successive pulses. Interference with a particular pulse can occur as a result of both past and future pulses, since the pulse is detected at the receiver after a mean path delay when the pulse is received with greatest strength. Portions of pulse energy from a past pulse that have experienced a greater than average delay may therefore interfere with a subsequent pulse, and portions of energy from a "future" pulse (i.e., a pulse that the radio receiver is not ready to detect) experiencing a less than average path delay may interfere with the present pulse being detected by the radio receiver.
As is known in the art, intersymbol interference may be greatly reduced using an adaptive equalizer. In one type of equalizer, for example, time-shifted versions of the received signal are combined with the received signal according to appropriate weights to cancel future and past interference. Such an equalizer may be constructed using a transverse filter including a tapped delay line. The appropriate weights, according to which delayed signal replicas are combined with the presently received signal, are derived during what is known as equalizer training. During equalizer training, a known sequences of symbols is transmitted and the output of the equalizer in response to the known sequence of symbols is compared to the known sequence itself. In an iterative process, an adoption algorithm optimized to minimize the difference between the detected symbol sequence and the actual symbol sequence sets the weights of the equalizer. If the weights of the equalizer are properly set, the error will be reduced to a minimum level and the equalizer will be said to have converged. If for some reason the weights are not properly set, the error may actually increase and the equalizer will be said to have diverged.
In another well-known type of equalizer, the Viterbi equalizer, a set of weights representing the impulse response of the communications channel is derived using a transverse filter in substantially the same manner as described above. Using the channel estimate, received pulses are detected according to the Viterbi algorithm to yield symbols of maximum likelihood given the channel estimate.
Measurement of time dispersion can, for example, be used in a receiver to find out what the source of interference is. That is, measurement of time dispersion can be used to distinguish between interference from reflected rays that arrive at the receiver at a time that puts them outside the equalizer window, and other types of interference including cochannel interference and adjacent channel interference.
A measurement of time dispersion, here expressed in dB, is the carrier over reflection (COR) value, defined as ##EQU1## where E.sub.i is the energy measured inside the equalizer window of length T.sub.1 and E.sub.o is the energy outside the window, measured over the interval T.sub.2 -T.sub.1 (T.sub.2 &gt;T.sub.1). These parameters are illustrated in FIG. 1, which is an exemplary graph of impulse response plotted as a function of time. The time intervals T.sub.1 and T.sub.2 should be specified as an integer number of modulation symbol intervals, T.sub.s. In Europe's standard Global System for Mobile communication (GSM), for example, T.sub.s is 3.69 .mu.s. The selection of values for T.sub.1 and T.sub.2 are not restricted, but higher values of T.sub.2 would presumably give lower accuracy in time dispersion measurements.
One possible way of measuring the energy inside the T.sub.1 and T.sub.2 -T.sub.1 window is by correlation of the received signal with a known training sequence. The energy in the T.sub.1 window and the energy in the T.sub.2 -T.sub.1 window are each calculated by adding the energy of the correlation values inside the respective windows. The time dispersion is measured by comparing the energy in the T.sub.1 window with the energy in the T.sub.2 -T.sub.1 window. Known training sequences are specified to be included, for example, in bursts that may occur, for example, in time slots of time division multiple access (TDMA) frames that are broadcast in, accordance with the GSM standard. Correlation of the received signal with the known training sequence is already performed in existing systems in order to find the synchronization position, that is, the position of the equalizer window.
The above-described measurement technique seems straightforward, but a number of problems stand in the way of using this technique to obtain a COR estimate. In particular, if the training sequence is of limited length compared to the time dispersion at hand, the correlation signal is an accurate measure of time dispersion only when it is based on portions of the received signal that are close to the main part of the received energy, that is, within and close to the equalizer window. Further away, the correlation properties of the training sequence are not very good.
There are three primary reasons why a correlation measure cannot be used to estimate the time dispersion. These are:
1) Contributions to the correlation estimate of a tap from signal energy that is received in another tap, when the two taps are separated more than the span of the ideal part of the training sequence's autocorrelation function. In GSM, for example, the training sequence has ideal (white) autocorrelation properties up to a separation of five taps. Taps separated by more than that can, therefore, not be estimated independently without interfering with each other. PA1 2) Contributions to the correlation estimate of a tap from correlation with received samples corresponding to bits outside of the training sequence (that are unknown). In the GSM example, when the training sequence is twenty-six bits long (normal burst), this error dominates when a tap is estimated that is separated more than fifteen taps from the main tap (i.e., the one with the most energy). PA1 3) Received interference (e.g., noise, cochannel interference, adjacent channel interference, interference from user signal energy received outside the equalizer window, plus any other interference received) that contributes to channel estimation errors.
If the interference level and the channel characteristics within the equalizer window were known, it would be possible to calculate accurate estimates of the three effects above and to subtract them from the channel estimate. In practice, however, the interference level and channel characteristics are not known, but instead have to be estimated. These estimates will be distorted if there is time dispersion outside the equalizer window, which of course there is because this is what we are attempting to measure.
The errors in the channel estimate that is made from the correlation between the received signal and the known training sequence are too large to be ignored. Consequently, a good estimate of the impulse response and thereby the time dispersion is impossible to get this way.
It is therefore desirable to provide techniques and apparatus for making accurate measurements of time dispersion.